Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites
ABSTRACT
Aim The accurate mapping of forest carbon stocks is essential for understanding
the global carbon cycle, for assessing emissions from deforestation, and for rational
land-use planning. Remote sensing (RS) is currently the key tool for this purpose,
but RS does not estimate vegetation biomass directly, and thus may miss significant
spatial variations in forest structure. We test the stated accuracy of pantropical
carbon maps using a large independent field dataset.
Location Tropical forests of the Amazon basin. The permanent archive of the field
plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/
2014_1
Methods Two recent pantropical RS maps of vegetation carbon are compared to
a unique ground-plot dataset, involving tree measurements in 413 large inventory
plots located in nine countries. The RS maps were compared directly to field plots,
and kriging of the field data was used to allow area-based comparisons.
Results The two RS carbon maps fail to capture the main gradient in Amazon
forest carbon detected using 413 ground plots, from the densely wooded tall forests
of the north-east, to the light-wooded, shorter forests of the south-west. The
differences between plots and RS maps far exceed the uncertainties given in these
studies, with whole regions over- or under-estimated by > 25%, whereas regional
uncertainties for the maps were reported to be < 5%.
Main conclusions Pantropical biomass maps are widely used by governments
and by projects aiming to reduce deforestation using carbon offsets, but may have
significant regional biases. Carbon-mapping techniques must be revised to account
for the known ecological variation in tree wood density and allometry to create
maps suitable for carbon accounting. The use of single relationships between tree
canopy height and above-ground biomass inevitably yields large, spatially correlated
errors. This presents a significant challenge to both the forest conservation
and remote sensing communities, because neither wood density nor species assemblages
can be reliably mapped from space.
MITCHARD E. T. A.;
FELDPAUSCH Ted;
BRIENEN R;
LOPEZ-GONZALEZ G;
MONTEAGUDO Abel;
BAKER T;
LEWIS S;
LLOYD J;
QUESADA Carlos A.;
GLOOR Manuel;
TER STEEGE Hans;
MEIR P.;
ALVAREZ Esteban;
ARAUJO-MURAKAMI Alejandro;
ARAGÃO Luiz E. O. C.;
ARROYO Luzmila;
AYMARD G;
BANKI O;
BONAL Damien;
BROWN Sandra;
BROWN Foster I.;
CERÓN Carlos E.;
MOSCOSO Victor Chama;
CHAVE Jerome;
COMISKEY James A.;
CORNEJO Fernando;
MEDINA Massiel Corrales;
DA COSTA Lola;
COSTA Flavia R. C.;
DI FIORE Anthony;
DOMINGUES Tomas F.;
ERWIN Terry;
FREDERICKSON Todd;
HIGUCHI Niro;
CORONADO Euridice N. Honorio;
KILLEEN Tim J.;
LAURANCE William F;
LEVIS Carolina;
MAGNUSSON William E.;
MARIMON Beatriz S.;
JUNIOR Ben Hur Marimon;
POLO Irina Mendoza;
MISHRA Piyush;
NASCIMENTO Marcelo T.;
NEILL David;
VARGAS Mario P. Núñez;
PALACIOS Walter A.;
PARADA Alexander;
MOLINA Guido Pardo;
PEÑA-CLAROS Marielos;
PITMAN Nigel;
PERES Carlos A.;
POORTER Lourens;
PRIETO Adriana;
RAMIREZ-ANGULO Hirma;
CORREA Zorayda Restrepo;
ROOPSIND Anand;
ROUCOUX Katherine H.;
RUDAS Agustin;
SALOMÃO Rafael P.;
SCHIETTI Juliana;
SILVEIRA Marcos;
DE SOUZA Priscila F.;
STEININGER Mark K.;
STROPP CARNEIRO Juliana;
TERBORGH John;
THOMAS Raquel;
TOLEDO Marisol;
TORRES-LEZAMA Armando;
VAN ANDEL Tinde R.;
VAN DER HEIJDEN Geertje;
VIEIRA Ima C. G.;
VIEIRA Simone;
VILANOVA-TORRE Emilio;
VOS Vincent A.;
WANG Ophelia;
ZARTMAN Charles E.;
MALHI Yadvinder;
PHILLIPS Oliver L.;
2016-11-18
WILEY-BLACKWELL
JRC94032
1466-822X,
http://onlinelibrary.wiley.com/doi/10.1111/geb.12168/abstract,
jsessionid=36767025612453FC6E376E1120DEF151.f04t01,
https://publications.jrc.ec.europa.eu/repository/handle/JRC94032,
10.1111/geb.12168,
Additional supporting files
| File name | Description | File type | |
|---|
